Gil Press, Contributor
As the big data analytics market rapidly expands to include mainstream customers, which technologies are most in demand and promise the most growth potential? The answers can be found in TechRadar: Big Data, Q1 2016, a new Forrester Research report evaluating the maturity and trajectory of 22 technologies across the entire data life cycle. The winners all contribute to real-time, predictive, and integrated insights, what big data customers want now.
Here is my take on the 10 hottest big data technologies based on Forrester’s analysis:
- Predictive analytics: software and/or hardware solutions that allow firms to discover, evaluate, optimize, and deploy predictive models by analyzing big data sources to improve business performance or mitigate risk.
- NoSQL databases: key-value, document, and graph databases
- Search and knowledge discovery: tools and technologies to support self-service extraction of information and new insights from large repositories of unstructured and structured data that resides in multiple sources such as file systems, databases, streams, APIs, and other platforms and applications.
- Stream analytics: software that can filter, aggregate, enrich, and analyze a high throughput of data from multiple disparate live data sources and in any data format.
- In-memory data fabric: provides low-latency access and processing of large quantities of data by distributing data across the dynamic random access memory (DRAM), Flash, or SSD of a distributed computer system.
distributed file stores: a computer network where data is stored on more than one node, often in a replicated fashion, for redundancy and performance.
